Papers
7
Total Citations
58
H-Index
3
About
Yi-Feng Chen is a leading researcher at the intersection of neurorehabilitation, robotics, and brain-computer interfaces. His work focuses on restoring motor function for neurologically impaired individuals, particularly stroke survivors, through innovative neurotechnology and robotic systems. Chen’s major contributions include developing methods to enhance neuroplasticity for post-stroke motor recovery, with his most-cited paper (31 citations) providing a comprehensive framework for combining neuromodulation with rehabilitation robotics. He has pioneered the use of functional near-infrared spectroscopy (fNIRS) for real-time neurofeedback in robot-assisted training, demonstrating its within-session reliability (9 citations). His research extends to practical applications like robot-assisted haptic rendering for instrumental activities of daily living (IADLs), such as nail hammering (8 citations), and novel EEG-based paradigms for classifying compound-limb movement intentions. Chen has also advanced continuous prediction of knee joint trajectories from sEMG signals and achieved physician-level performance in robot-assisted ankle rehabilitation through imitation learning. His notable work includes developing sensing equivalent kinematics for mirror rehabilitation therapy, showcasing his commitment to translating cutting-edge research into clinically viable solutions that improve patient outcomes and independence.
Research Focus
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